Image Classification and Text Identification in Inspecting Military Aircrafts Logos: Application of Convolutional Neural Network

Saleh Edhah, Abeer Awadallah, Mayar Madboly, Hamdihun Dawed, Naoufel Werghi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Object detection and inspection using images or videos have been receiving increased attention in many applications such as traffic control, brand monitoring, trademark compliance, and product authentication. A particular application that is currently a topic of interest is aircraft logo detection, which aims at automating the visual inspection carried out manually by aircraft engineers. Aircraft logos should meet a large set of requirements that include geometric constraints on the logo elements and patterns, and constraints on the position and orientation with respect to specific references. This work considers the design of a high accuracy convolutional neural network to detect and classify aircraft logos as either adequate or inadequate based on specified criteria. The performance of the developed network is compared to a number of classical machine learning algorithms to demonstrate its effectiveness. Adequate logos are then processed further by extracting them from a frame using robust features extraction algorithm and determining their orientation angle with respect to the horizontal reference axis. Afterward, a text detection technique using a character region awareness for text detection algorithm implemented on a pre-trained network is carried out, along with optical character recognition tool to detect and extract the text from the logos for further processing in other applications. The developed network is tested on actual aircraft logos, captured from the field, where satisfactory results are obtained.

Original languageBritish English
Title of host publicationIEEE International Symposium on Robotic and Sensors Environments, ROSE 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665489232
DOIs
StatePublished - 2022
Event15th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2022 - Virtual, Online, United Arab Emirates
Duration: 14 Nov 202215 Nov 2022

Publication series

NameIEEE International Symposium on Robotic and Sensors Environments, ROSE 2022 - Proceedings

Conference

Conference15th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2022
Country/TerritoryUnited Arab Emirates
CityVirtual, Online
Period14/11/2215/11/22

Keywords

  • Character Region Awareness for Text Detection
  • Classification
  • Convolutional Neural Network
  • Deep Learning
  • Logo Detection
  • Optical Character Recognition
  • Transfer Learning

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